A semantic network is a network that represents semantic relations among terms (e.g., concepts). A semantic network may be used as a form of knowledge representation, and therefore may be used to model business knowledge in companies and their various parts, e.g. as enterprise knowledge and/or terminology.
The typical usage may be in search engines, where the network may be used within different techniques to identify the meaning of the term and/or sentence. Mainly the search terms are defined as words in some order or relation. The searched term may then be interpreted by the search engine as a string/term. For example, the search result for “Lotus” may be divided into results about “Lotus” as a model of a car, “Lotus” as a brand of car oil, and “Lotus” as a flower. In this situation, there are different knowledge domains. The knowledge domains can be ordered hierarchically, which allows for knowledge grouping, e.g. the first two meanings may belong to similar knowledge groups, and the last one has nothing in common and is defined in a completely different context/knowledge group (e.g., as a flower).
In this application, some modeling solutions are used to define the context of particular terms/information. Knowledge domain group terms may be organized and belong to the same knowledge area or expertise area, for example: IT, finance, etc. The knowledge area or expertise area may be grouped into knowledge domains and may be used to specify the context of the required information and therefore deliver data with better quality. Typically the business knowledge and the terminology used is distributed throughout the entire company, experts within the company, management heads, and large volumes of documents, etc. The main problem is how to detect and determine used business terminology and then consolidate it in a domain-oriented semantic network.
From another side, the modern business applications are built from business objects that group or encapsulate the definition of relevant business content information. A business object structural model may contain one root node and zero to many business object nodes. The node's hierarchy (i.e. tree) may be built using associations between business object nodes that group semantically related attributes. Additionally, each attribute may be structurally defined by an underlying global data type—so-called element data type or global data type (centrally defined data type). Finally, the instances of business objects provide business-related terminology, e.g. a material business object provides the definition of material and the material names used and defined in a particular company.